Bots! What Are They Good For?
Lizzie O’Leary: When I got Sam Wylie on the line, I asked him to help me look for bots on Twitter.
Speaker 2: Okay, let’s look. Okay. Wow. Elon Musk has 97.1 million followers. That is a heck of a lot of Twitter followers for anyone.
Lizzie O’Leary: Specifically bots that follow Elon Musk, Sam’s assistant professor in the journalism school at the University of Texas in Austin. He’s also the co-author of a new book, literally titled Bots.
Speaker 2: And I’m going to go to this site Bought Meter, which is kind of the industry standard for checking for bot followers. It looks like his score in terms of like bot like followers is a 1.1 out of five according to their rankings.
Lizzie O’Leary: And what does that mean?
Speaker 2: I mean, basically what I’m seeing on Elon Musk’s follower scores are that about roughly about 20% of of Elon’s followers have some bought like looking activity.
Lizzie O’Leary: And do you want to check me while we’re at it so we can compare us?
Speaker 2: Yeah, sure. Why not? Let’s do.
Lizzie O’Leary: It. Okay, so I’m Lizzie. Oh, really easy. IEEE 0hreally.
Speaker 2: Okay, I like that. That’s a good play on words. Here we go. Yeah. So your your score is significantly better on bottom. Either you’re getting a 0.2 out of five.
Lizzie O’Leary: Which means I have a lower proportion of bot followers than Musk. Does that make sense? Bots tend to follow big accounts, and I have 67,000 followers compared to his 97 million. I did have some, though.
Speaker 2: Okay. Well, yeah, you definitely have some followers that look to be bought, like some of them are. Sorry, I’m looking at some of the profile pictures and they’re really, really funny.
Lizzie O’Leary: But are they all like Forni?
Speaker 2: Yeah, what we call that’s kind of a horrible thing, but they call them bots. So yeah, there’s there’s a lot of pictures of women in underwear and then like, yeah, like the classic Twitter photos and things like that. So, so yeah, I’m also for you getting about 18% about followers.
Lizzie O’Leary: So not as bad as Isla.
Speaker 2: Not as bad as Elon. I expected Elon to have more bot followers. Actually, I’m, I’m going to run it through another service and see what we can find.
Lizzie O’Leary: I saw one estimate that more than two thirds of Musk’s followers were bots or spam accounts. Sam tried another service which found something similar.
Speaker 2: Yeah, it says 70% fake followers. So 67 million of his followers are fake.
Lizzie O’Leary: It’s hard to know which estimate is right. 20% or 70% or something in between. But it’s clear that if you have a popular account, bots will follow you. What did you think when you saw Elon tweeting about how spam and fake accounts might be the reason that he pulls out of this deal to buy Twitter.
Speaker 2: Personally, I mean, personally and professionally, I thought it was really contradictory. Elon Musk has talked a lot in the last several weeks about how he would not institute any permanent bans on Twitter. But then out of the other side of his mouth, he said suddenly that he wants to get rid of bots on Twitter and that he may not buy the company because there’s so many bots.
Lizzie O’Leary: Whether or not you believe Elon Musk, that bots are what’s threatening this deal, Sam says this conversation is focused on the wrong thing.
Speaker 2: People always run bots. Bots are just a tool to automate an account. And so the idea that bots in and of themselves are bad or that any bot constitutes spam is simply wrong.
Lizzie O’Leary: So today on the show bots, what are they good for? I’m Lizzie O’Leary and you’re listening to what next? TBD a show about technology, power, and how the future will be determined. Stick with us.
Lizzie O’Leary: It’s worth defining exactly what a bot is. And Sam, after all, wrote the book on this. Here’s what he and his co-author, Nick Monaco, came up with.
Speaker 2: Our definition of a bot is any automated software program that is used to do tasks online that a person would otherwise have to do. There’s lots of tasks that would be so monotonous and also so gargantuan that people wouldn’t even be able to do them. So automated software programs have to do those tasks.
Lizzie O’Leary: Like what?
Speaker 2: Like scraping Google to find new websites. So like scraping through all the different data that exists on the web to try to make sure that the ranking system on Google works properly.
Lizzie O’Leary: But decades before Google there was Eliza. Eliza was a natural language processing bot created at MIT in the 1960s.
Speaker 2: Eliza has a computer program that anyone can converse with via the keyboard, and it’ll reply on the screen.
Lizzie O’Leary: Men are all alike. In what way? They’re always bugging us about something or other.
Speaker 2: Can you think of a specific example? Later on, Eliza was followed by a bot called Dr.. And basically would like ask people questions like things like how does that make you feel? Like, Oh, that’s interesting. And so these are early examples of what you might call a chat bot, and there’s a lot of chat bots online. Most of them are really, really rudimentary.
Lizzie O’Leary: Yeah. I mean, any time you are like interacting with maybe a health insurance company or your cell phone provider, like that little chat bot window pops up because it’s easier for them to do that than have you talk to a human.
Speaker 2: Yeah, there’s there’s been a lot of reporting out there that sort of like talks about bots as if we’re in this like Brave New World of Terminator. I like these these smart bots that are out there, like manipulating public opinion and getting us to vote for particular politicians by chatting with us. And that’s simply not the case. I wrote a book awhile back called The Reality Game, and in that book, the research I did showed that over and over and over again based upon a review. The most intelligent A.I. system that exists as a chat bot basically has the intelligence of a five year old and five year olds can be manipulative, but they’re not going to get you to change your political affiliation usually unless they say something particularly incisive on accident.
Lizzie O’Leary: But what can get people to change their minds is a flood of information, like seeing the same message over and over again on social media, creating an illusion of popularity.
Speaker 2: So if you get 20,000 bots talking on a particular topic or using a particular hashtag, it makes that thing look more popular than it actually is. And the quantitative metrics that get used to generate those Twitter trends or YouTube trends then say, Oh, look, this thing’s popular. A great example of that, a very sad example is the day of the Parkland shooting. The hashtag about David Hogg being a character actor was the number one trending hashtag on YouTube. And YouTube put it on its home page on its homepage. But later on, researchers showed that that was hugely driven by bots.
Lizzie O’Leary: While bots get a bad name on social media because they can spread disinformation, there are also bots built to help consumers or engage in advocacy. Basically, they’re created to make things easier for people.
Speaker 2: There’s bots, for instance, that are that have been built to help people in an automated fashion fight their parking tickets. So you can basically plug in the number of the ticket and the bot will contest it for you and has quite a high success rate in certain municipalities of overturning the tickets for people without them having to go through the bureaucracy. Bots have been built that are used to amplify voices that are otherwise marginalized. So for instance, like bots that promote awareness about voting or bots that are used to promote awareness about Black Lives Matter. I know a lot of people in journalism that have built bots that will pass large data sets for them so that they can figure out, you know, say like the Panama Papers, if you need to figure out what kind of data in there was actually germane to your reporting about the.
Lizzie O’Leary: Abuse and thousands of tax records and looking through, you know, all of these offshore tax havens.
Speaker 2: Precisely like if you’re going to actually get to go through that, you need a tool that’s going to help you to do it. And the bot is the tool that’s going to help you do it.
Lizzie O’Leary: Even though the terms sometimes get conflated, especially in big societal debates like the one Elon Musk has sparked. It’s worth noting that not every fake account on the internet is a bot. So an account like Italian Elon Musk that tweets out things like I send the Canal Zone into space. This is. This is not about.
Speaker 2: Not necessarily. Oftentimes, people look at accounts like that and instantaneously think that it’s a lot just because it’s it’s garbled or it’s odd. But oftentimes those kinds of accounts can be run by people. It’s just that they’re anonymous people that are doing that. And we call those kinds of accounts sock puppets. So they’re they’re run by a person, but the person is not revealing their actual identity. So it’s not like, you know, Lizzie O’Leary or Samuel Willey’s account.
Lizzie O’Leary: Right now, Elon Musk is claiming that Twitter hasn’t been open with him about how many bots and fake accounts exist on the platform. After he complained about it in a securities filing, the company essentially said, Fine, you can have access to our full firehose of data and figure it out yourself. But perhaps ironically, Sam says the reason that Twitter has an issue with bot and spam accounts is the transparent way it was built.
Speaker 2: So Twitter has has has had historically had an open API, which has meant that that, you know, yes, developers can build bots onto Twitter in a quite easy fashion. And so that was one way a lot of bots got created there. But also it meant that researchers could study Twitter easily allowing researchers and journalists and developers onto their platform to analyze data on Twitter means that there’s tons of information out there on how many bots there are on Twitter. Facebook does not do that. YouTube does not do that. They do not allow that kind of access. In fact, one of the main gripes from researchers like me is that a lot of the major social media platforms other than Twitter allow very little access to data. So the question about how many bots there are on those platforms is just a big question mark.
Lizzie O’Leary: There is another question here that’s important when you’re trying to figure out how valuable a company like Twitter is. Platforms like Twitter make money based on their number of active users. So do bots distort those numbers?
Speaker 2: I mean, it’s an argument I’ve been making for a really long time in my own research that like, you know, the amount of bots in your platform kind of dictates can dictate an increase in audience engagement, and that includes advertising engagement. So it basically it undercuts the bottom line because advertisers hate fake traffic. They want actual real eyeballs of people that are going to buy their stuff ideally.
Speaker 2: My perception after like following this coverage for the last several weeks and listening to Elon Musk, but also knowing what I know about Twitter and what Twitter has done about it, spot problem. It leads me to believe that Elon is using this issue of bots as kind of a backdoor to get out of the deal because Twitter is arguably the industry leader in combating influence operations, disinformation and bot operations. Twitter has for a long time been transparent. I think that Elon Musk is seizing upon a major critique of Twitter that would that would potentially undercut Twitter’s engagement and its advertising mechanism.
Speaker 2: However, amongst the other social media companies, Twitter is doing pretty good on this. I think Twitter has done very well over time. And that’s the crucial thing. And we know that Twitter has done Big Bopper duties. There was one in 2018, for instance, where people noticed a huge drop in their account numbers because Twitter just went wholesale and deleted millions of bot accounts. And so Twitter hasn’t been bashful about doing this, and they’ve been very transparent about the fact that they’re doing it.
Lizzie O’Leary: When we come back, are bots profitable?
Lizzie O’Leary: I want to unpack a little bit the relationship between. But and and moneymaking because listening to you on the one hand, you know, the business model is centered around ad engagement and it seems like more bots would would equal more engagement. But on the other hand, add engagement comes from engagement from people who are interested in the advertisement. So like, how, how do you pull those things apart? Do bots make money?
Speaker 2: Bots can be used to make money because because the Internet is a it’s a computational system. It runs on quantitative metrics and it runs on numbers. And social media is is no different in many ways. So take take a site like YouTube. The more popular you get as an influencer on YouTube and the more engagement you get on YouTube, the more money you make every month. And so if you can figure out a way to generate automated engagement that doesn’t get detected by the platform, you can become quite rich. And so, you know, there’s that famous saying about nobody knowing you’re a dog.
Lizzie O’Leary: On the Internet.
Speaker 2: Yeah, nobody knowing you’re a dog on the Internet. A better saying would be nobody knows you’re a bot on the Internet. It’s really, really hard to parse for for many firms and for even the leading researchers whether or not the more sophisticated bot accounts are actually bots or not. And it gets back to that problem that I was talking about earlier, which is that oftentimes accounts that are automated online are more akin to cyborgs. So people will step in oftentimes and you’ll see clearly human behavior if you’re tracking it on the back end. And so it’s really hard to know whether or not you’re going to delete this account because is it a person or is it a bot? Is it just someone that’s actually automating some degree of their presence online.
Lizzie O’Leary: Debate to make money for Twitter?
Speaker 2: I think it’s inarguable that bots have generated revenue for Twitter over the course of its company’s history because Twitter has has definitely had a huge problem. And so the numbers of thoughts on the platform, researchers have have made claims that the numbers of bots on the platform are far higher than what Twitter releases to the Securities and Exchange Commission every year.
Lizzie O’Leary: Which is about 5%, they say.
Speaker 2: Yeah. And some researchers have have, you know, said it said as many as half of the people on Twitter are bots. But I think I think that’s a way overblown. More reason to researchers would say you know it’s it’s maybe 15% or 20% of of the traffic on Twitter is bots and we know that the majority of bots on Twitter are spam bots and are commercially motivated.
Lizzie O’Leary: So even if Musk is using this as a smokescreen to get out of the deal, he’s kind of making maybe a decent point.
Speaker 2: He’s making a decent point. It’s just that he’s kind of coming in at a time when a lot of progress has been made and kind of throwing out the baby with the bathwater. It’s simultaneously, like, gratifying to me to see him saying this and really frustrating to see him saying this because it glosses over a lot of complexity and it also glosses over a ton of research and work that’s been done in InfoSec, but also by a lot of other social scientists and computer scientists to identify and help combat this issue at the social media firms.
Speaker 2: He talks in soundbites. He talks in a way that suggests that he hasn’t done his his background research. He doesn’t understand audience engagement. He doesn’t understand the issues of data security on Twitter and, you know, the chatter on Twitter and off of Twitter amongst the kind of info security crowd, infosec crowd, is that a lot of people are really scared if it would be very, very scared if he bought Twitter because it could potentially result in a lot of regression in policies that have been that have been made not just on bots, but in a lot of other things.
Lizzie O’Leary: On Tuesday, the Texas Attorney General, Ken Paxton, waded into this whole mess, saying that the state was investigating the bot issue because it might hurt Texas businesses and consumers. What do you make of that?
Speaker 2: I’m here in Texas, and I follow Texas politics pretty closely. And, you know, the long and short of it is that it seems to be a blatantly political move. Ken Paxton has been has talked about his concerns about conservatives being silenced on social media a lot and has kind of tried to tie Texas boat to Elon Musk’s purchase of Twitter in a way that, you know, that riffs off of of Musk’s statements about Donald Trump and certain bands of certain people. But the frank thing is, is that the research does not back up what Ken Paxton is saying. And, you know, the scientific work that’s been done does not show that conservatives are being silenced on Twitter or Facebook. In fact, there’s quite a bit of scientific, good scientific research out there that shows that some conservative voices are unduly amplified on these sites.
Lizzie O’Leary: I guess one question I have about the Paxton issue is, is that does this actually mean anything for the Twitter deal or is it just this sort of symbolic twinning of the interests of Elon Musk and the Republican Party, certain parts of the Republican Party, as they have glommed onto Musk as a sort of, quote unquote, champion of free speech.
Speaker 2: I think that Paxton’s move is definitely glomming on to the headline grabbing that Elon Musk has done what Elon has done. It seems like it is used at least partially the purchase of Twitter to talk about a lot of political issues that have gotten him a lot of attention. And Ken Paxton is is no fool. He understands that by by proposing these kinds of laws and by talking about these kinds of things that he’s appealing to his base, he’s appealing to the anger that has really been directed specifically at Twitter after the deletion of Donald Trump’s Twitter account.
Lizzie O’Leary: One thing that that I have been thinking about a lot is how our own social media timelines, particularly Twitter, they’re so particular to us. And I think sometimes we forget that other people’s look totally different. My husband’s Twitter timeline is full of pilots talking about aviation, and mine is a lot of journalists like tweeting, really dark, weird jokes. And what Elon Musk must see when he opens his Twitter is is completely different. And yet we all think that there is some singular shared reality called Twitter. And I wonder how possible it is to make policy, whether it’s about bots or spam accounts, when our realities and our followers and the makeup of who they are are so different.
Speaker 2: There’s a lot of different subsections of Twitter that exist not only within the United States, but internationally. So Twitter doesn’t only occur in English. It occurs in so many other languages. Right. And their experience of Twitter looks way different than the experience of Elon Musk or Ken Paxton or me.
Lizzie O’Leary: Like middle aged white mom.
Speaker 2: Or you or you, Lizzie or me, you know. And that means that laws and policies that get made, that police certain modes of communication on Twitter need to be socially and culturally contextual. They need to think about how different types of people in different places use Twitter. There are things that can be done that are universally beneficial to users. However, deleting blatant lies about how, when or where to vote. You know, that I think is probably pretty universally beneficial to all people in the United States. We do not want lies about how, when and where to vote to be shared on Twitter. But that doesn’t mean that there’s not a huge need for nuance, not only in external policy, but also in Twitter’s internal policy. And frankly, we haven’t seen the nuance that I would hope for and that many researchers have been calling for for well over a decade.
Lizzie O’Leary: Does all this kind of light and heat on this issue mean that that Twitter needs to to put in a little more effort here?
Speaker 2: If you look at Twitter and you look at its size and you look at the money that it has comparatively when when satellite alongside Facebook or YouTube. Twitter has done way more. The better question would be, could Twitter benefit from from more money being put on this and where could they get it? You know what I mean? Like, because the answer is yes. And then the answer is. Big question, mark. I don’t know. Like if Elon Musk had been saying, I want to buy Twitter and I’m going to put, you know, hundreds of millions of dollars towards, you know, the kind of content, moderation and moderation and spam moderation we’re talking about. People like me would be really excited because Twitter needs that.
Lizzie O’Leary: Samuel Wiley, thank you so much for your time.
Speaker 2: Thanks so much for having me. It’s been fun.
Lizzie O’Leary: Samuel Wooley is an assistant professor in the School of Journalism at the University of Texas at Austin. He’s also the project director for propaganda research at the Center for Media Engagement at UT. That is it for the show today. TBD is produced by Evan Campbell. Our show is edited by Tori Bosch. Joanne Levine is the executive producer for what next? Alisha Montgomery is vice president of Audio for Slate. TBD is also part of the larger what next family, and we’re part of Future Tense, a partnership of Slate, Arizona State University and New America. We’ll be back on Sunday with another episode. I’m Lizzie O’Leary. Thanks for listening.
